Lagotto allows a user to aggregate relevant performance data on research articles, including how often an article has been viewed, cited, saved, discussed and recommended. The application was called Article-Level Metrics (ALM) until September 2014 and was started in March 2009 by the Open Access publisher Public Library of Science (PLOS). We are continuing to expand Lagotto because we believe that articles should be considered on their own merits, and that the impact of an individual article should not be determined by the journal in which it happened to be published. As a result, we hope that new ways of measuring and evaluating research quality (or ‘impact’) can and will evolve. To learn more about Article-Level Metrics, see the SPARC ALM primer.
Lagotto uses Vagrant and Virtualbox for setting up the development environment. To start developing now on your local machine (Mac OS X, Linux or Windows):
- Install Vagrant: https://www.vagrantup.com/downloads.html
- Install Virtualbox: https://www.virtualbox.org/wiki/Downloads
- Clone this repository
git clone git@github.com:articlemetrics/lagotto.git - Cd into it
- Copy the file
.env.exampleto.envand make any changes to the configuration as needed - Run
vagrant up
Once the setup is complete (it might take up to 15 minutes), you'll be able to open up a browser and navigate to http://10.2.2.4, and you should see this screen:
Detailed instructions on how to start developing are here. There is extensive documentation - including installation instructions - at the project website.
You should follow @plosalm on Twitter for announcements and updates.
Please direct questions about the application to the discussion forum.
- Fork the project
- Write tests for your new feature or a test that reproduces a bug
- Implement your feature or make a bug fix
- Do not mess with Rakefile, version or history
- Commit, push and make a pull request. Bonus points for topical branches.
Lagotto is released under the MIT License.